Triple

T34165136
Position Surface form Disambiguated ID Type / Status
Subject Roxas City Bandstand E876388 entity
Predicate locatedInArea P40 FINISHED
Object Roxas City Plaza
Roxas City Plaza is a central public square in Roxas City, Philippines, known as a civic and cultural hub surrounded by historic landmarks and community gathering spaces.
E2084274 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Roxas City Plaza | Statement: [Roxas City Bandstand, locatedInArea, Roxas City Plaza]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Roxas City Plaza
Triple: [Roxas City Bandstand, locatedInArea, Roxas City Plaza]
Generated description
Roxas City Plaza is a central public square in Roxas City, Philippines, known as a civic and cultural hub surrounded by historic landmarks and community gathering spaces.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f349ac987481908a8e6053f665bc8b completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70fdedf708190ab68c2d567e086d0 completed May 3, 2026, 9:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36c1d7070c8190bd08e16196c67256 completed June 20, 2026, 4:37 p.m.
NEDg Description generation batch_6a36c265a4588190b415159def7d4690 completed June 20, 2026, 4:40 p.m.
NED2 Entity disambiguation (via description) batch_6a36c4cc187081908cd56a998ab5c90d completed June 20, 2026, 4:50 p.m.
Created at: May 1, 2026, 1:54 a.m.